feat: Echo + Epistemic effect inference (ADR-0009 D1+D2, slices 1+2)

[hyperpolymath]

(b) effect inference — slices 1+2 (additive, non-breaking). Implements the inference half of ADR-0009 — both graded function effects.

Echo effect (D1) — echo::function_echo(body) -> Echo

The Echo grade a function body induces, as the join of its statements' echoes: addition-only assignment → Safe; reverse/reversible blocks → their block echo (classify_stmts); control flow → join of sub-bodies. Reuses the existing idempotent Echo::join; the block-level classify_stmts becomes the body-aggregate special case. Telling test: reverse { x += x } in a body → the function is Neutral.

Epistemic effect (D2) — epistemic::function_epistemic(func) -> Epistemic

The dual axis (what a function reveals about its inputs), lattice Opaque ⊑ Partial ⊑ Transparent, join = worst-case revelation. v1 inference (conservative): grade by the worst-case revelation across the function's output expressions (return/print) — an output that is a parameter → Transparent, one referencing a parameter → Partial, one independent → Opaque; no outputs → Opaque. Refine on use, per ADR-0009.

Scope

Inference only — neither grade is yet stored in FunctionDecl/TypeAnnotation::Function or joined across FunctionCalls. That call-resolution + type-wiring is the next (more invasive) slice. Kept additive so it can't destabilise the build.

10 tests (4 echo + 6 epistemic); clippy -D warnings clean; #[forbid(unsafe_code)]. No unwrap_or (avoids Hypatia's dangerous-default rule).

Next: wire the (echo, epi) row into function types + call resolution; then mechanise in JtvEcho.lean; then number-systems.

https://claude.ai/code/session_01BJmfoz1ZS1Pejy9LLMY742

[github-actions]

🔍 Hypatia Security Scan

Findings: 51 issues detected

Severity	Count
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🟡 Medium	26

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[github-actions]

🔍 Hypatia Security Scan

Findings: 51 issues detected

Severity	Count
🔴 Critical	0
🟠 High	25
🟡 Medium	26

View findings

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